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Performance function mse was modified to msereg.
The scalar μ decreases after each successful step (reduction in the performance function) and increases only when a tentative step would increase the performance function.
Thus, λ is decreased after each successful step (reduction in performance function) and is increased only when a tentative step would increase the performance function.
Thus, μ is decreased after each successful step (reduction in performance function) and is increased only when a tentative step would increase the performance function.
The performance function minimization problem with polynomial matrix inequalities is then transformed into a problem of minimizing a convex performance function involving standard LMIs.
Therefore, performance function can be defined as: Z=Rhbox S (11).
It is multiplied by mu_inc whenever a step would increase the performance function.
This value is multiplied by mu_dec whenever the performance function is reduced in a step.
It is multiplied by mu increase whenever a step would increase the performance function.
In this way, the performance function will reduce at each iteration of the algorithm [13].
The mean squared error performance function is selected to estimate the ANN performance.
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